Human body three-dimensional size information prediction method and device based on GA-BP-MC neural network
A GA-BP-MC, three-dimensional size technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as difficulty in accurately predicting human body circumference information
Active Publication Date: 2020-10-23
WUHAN TEXTILE UNIV
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[0005] The purpose of the present invention is to provide a method and device for predicting human body three-dimensional size information based on GA-BP-MC neural network, which effectively solves the technical problem that it is difficult to accurately predict human body circumference information in the prior art
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[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, specific embodiments of the present invention will be described below with reference to the accompanying drawings. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention, and those skilled in the art can obtain other accompanying drawings based on these drawings and obtain other examples.
[0037] Such as figure 1 Shown is a schematic flow chart of an embodiment of the method for predicting human body three-dimensional size information based on GA-BP-MC neural network in the present invention. It can be seen from the figure that the method for predicting human body three-dimensional size information includes: S10 forming a training sample set , each set of training data in the training sample set contains multiple input parameters and a target three-dimensional size. The two-dimensional ...
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The invention provides a human body three-dimensional size information prediction method and device based on a GA-BP-MC neural network. The method comprises the steps: S10, forming a training sample set, and enabling each group of training data in the training sample set to comprise a plurality of input parameters and a target three-dimensional size; s20, constructing a multi-input BP network model containing a plurality of hidden layers; s30, optimizing the initial weight and threshold of the BP network model by utilizing a GA (Genetic Algorithm) to obtain the optimal weight and threshold ofthe individual; s40, training the BP network model based on the optimal weight and threshold of the individual and the formed training sample set, and determining model parameters; s50, inputting testdata containing the feature information of the user, the two-dimensional size of the preset part and the proportionality coefficient of the preset part relative to the height into a trained GA-BP network model to obtain a three-dimensional prediction size of the preset part; and S60, inputting the three-dimensional prediction size into the MC model for correction to obtain corrected three-dimensional size information, and completing accurate prediction of the three-dimensional size information of the preset part.
Description
technical field [0001] The invention relates to the technical field of computers and networks, in particular to a method and device for predicting three-dimensional size information of a human body. Background technique [0002] With the rapid development of information technology in the field of clothing, human body size measurement technology has gradually been applied in various technical fields such as personalized clothing customization and virtual fitting, and online non-contact human body size measurement plays an important role in the field of clothing customization. Crucial role. [0003] At present, the non-contact body size measurement technology is mainly based on the 3D body scanning system. However, due to problems such as high cost of measuring instruments and inflexible measurement locations, this technology cannot be widely popularized in the market. To meet the needs of SMEs, an image-based non-contact anthropometric method is proposed. [0004] In terms...
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IPC IPC(8): G06K9/46G06N3/04G06N3/08G06T17/00
CPCG06T17/00G06N3/08G06N3/049G06V10/44G06V10/462G06N3/044G06N3/045Y02P90/30
Inventor 胡新荣刘嘉文黄子寒刘军平彭涛张自力
Owner WUHAN TEXTILE UNIV